201811510210hjx's Stars
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
jindongwang/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
zhaoxin94/awesome-domain-adaptation
A collection of AWESOME things about domian adaptation
thuml/Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
dragen1860/MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
wangkai930418/awesome-diffusion-categorized
collection of diffusion model papers categorized by their subareas
KaiyangZhou/Dassl.pytorch
A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.
yfzhang114/Generalization-Causality
关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记
RL-VIG/LibFewShot
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
barebell/DA
Unsupervised Domain Adaptation Papers and Code
yinboc/few-shot-meta-baseline
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning, in ICCV 2021
cemoody/topicsne
t-SNE experiments in pytorch
Sha-Lab/FEAT
The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"
mxl1990/tsne-pytorch
Pytorch implementation for t-SNE with cuda to accelerate
brandontrabucco/da-fusion
Effective Data Augmentation With Diffusion Models
Fei-Long121/DeepBDC
The Pytorch code of "Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification", CVPR 2022 (Oral).
georgosgeorgos/few-shot-diffusion-models
Few-Shot Diffusion Models
hzvwsrexw15/echo
Chat GPT chrome extension Copilot
CSer-Tang-hao/Awesome-Fine-Grained-Few-Shot-Learning
The summary of code and paper for few-shot learning in fine-grained recognition
leftthomas/GradCAM
A PyTorch implementation of Grad-CAM based on ICCV 2017 paper "Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization"
DanielShalam/BPA
leesb7426/CVPR2022-Task-Discrepancy-Maximization-for-Fine-grained-Few-Shot-Classification
Official PyTorch Repository of "Task Discrepancy Maximization for Fine-grained Few-Shot Classification" (TDM, CVPR 2022 Oral Paper)
NWPUZhoufei/LDP-Net
Shaosifan/Remote-Sensing-Image-Super-Resolution-Papers
Han-Jia/LastShot
Layjins/SpatialFormer
Code for AAAI 2023 paper "SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning"
onlyyao/GLFA-SOLF
Global- and local-aware feature augmentation with semantic orthogonality for few-shot image classification (Pattern Recognition 2023)
SAINLP/CBPM
Code for paper "Few-shot relation classification using clustering-based prototype modification"
mzr1996/mmpretrain
OpenMMLab Image Classification Toolbox and Benchmark
NimaVahdat/Few-Shot-Learning
This is the implementation of the approach described in the paper "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions" by Ye, Han-Jia et al. The proposed approach adapts instance embeddings to the target classification task with a set-to-set function and achieves state-of-the-art results on multiple few-shot learning benchmarks.